Fifteen million people in the United States have Type 2 diabetes. In both human and economic terms, diabetes is one of the most costly diseases in the nation today. The cost of medical care and services to treat diabetes is estimated to have been $91.8 billion in 2002. Another $40.2 billion of lost productivity, disability and premature death is also attributable to the disease. One million new cases are diagnosed each year, and many people do not learn they have the disease until they develop one of its life-threatening complications, which include heart disease, stroke and kidney disease.
Diabetes has been attributed to both genetic and lifestyle factors, including obesity, age, sedentary lifestyle, hypertension, and use of drugs that block insulin action or antagonize insulin action. As a result, in the absence of a predictive diagnostic, single factors can not reliably be used to accurately assess an individual's propensity for developing the disease. Type 2 diabetes is typically diagnosed by measuring fasted plasma glucose, 2-hour plasma glucose or random plasma glucose (if symptoms are present). Persons with early—stage Type 2 diabetes are usually asymptomatic and may not realize they are ill; they may live for many years with uncontrolled diabetes before symptoms ever occur. When they do occur, those symptoms are often related to a life-threatening complication. Treatment or lifestyle changes in the early stages of disease can delay and possibly even prevent development of diabetes and its related complications.
Treatment for prediabetes can slow or reverse the disease in some individuals, particularly in early stage disease. Lifestyle intervention or treatment with, for instance, metformin in persons at high risk can reduce the incidence of diabetes by 58% and 31% respectively. Hence, a simple to administer method to monitor early stage disease progression, and determine efficacy of treatment, would greatly improve disease treatment and outcomes.
Type 2 Diabetes (non-insulin-dependent Diabetes or adult-onset Diabetes) results from insensitivity to insulin, and accounts for 90% of Diabetes worldwide. Gestational Diabetes is a loss of blood sugar control (hyperglycemia) that occurs during pregnancy. Type 2 Diabetes is characterized by disorders of insulin action and insulin secretion, either of which may be the predominant feature. Type 2 Diabetes patients are characterized with a relative, rather than absolute, insulin deficiency and are insulin resistant. At least initially, and often throughout their lifetime, these individuals do not need supplemental insulin treatment to survive. Type 2 Diabetes accounts for 90-95% of all cases of Diabetes and can go undiagnosed for many years because the hyperglycemia is often not severe enough to provoke noticeable symptoms of Diabetes or symptoms are simply not recognized. The majority of patients with Type 2 Diabetes are obese, and obesity itself may cause or aggravate insulin resistance. Many of those who are not obese by traditional weight criteria may have an increased percentage of body fat distributed predominantly in the abdominal region (visceral fat). Whereas patients with this form of Diabetes may have insulin levels that appear normal or elevated, the high blood glucose levels in these diabetic patients would be expected to result in even higher insulin values had their beta cell function been normal. Thus, insulin secretion is often defective and insufficient to compensate for the insulin resistance. On the other hand, some hyperglycemic individuals have essentially normal insulin action, but markedly impaired insulin secretion.
Pre-diabetics often have fasting glucose levels between normal and frank diabetic levels. Abnormal glucose tolerance, or “impaired glucose tolerance” can be an indication that an individual is on the path toward Diabetes; it requires the use of a 2-hour oral glucose tolerance test for its detection. However, it has been shown that impaired glucose tolerance is by itself entirely asymptomatic and unassociated with any functional disability. Indeed, insulin secretion is typically greater in response to a mixed meal than in response to a pure glucose load; as a result, most persons with impaired glucose tolerance are rarely, if ever, hyperglycemic in their daily lives, except when they undergo diagnostic glucose tolerance tests. Thus, the importance of impaired glucose tolerance resides exclusively in its ability to identify persons at increased risk of future disease (Stern et al., 2002).
Diabetes is generally diagnosed by determining blood glucose levels after fasting overnight (fasting plasma glucose level) or by determining blood glucose levels after fasting, followed by ingestion of glucose and a blood glucose measurement two hours after glucose administration (a glucose tolerance test). In studies conducted by Stern and colleagues (Stern et al., Diabetes Care 25:1851-1856 (2002)), the sensitivity and false-positive rates of impaired glucose tolerance as a predictor of future conversion to Type 2 Diabetes was 50.9% and 10.2%, respectively, representing an area under the Receiver-Operating Characteristic Curve of 77.5% (with a 95% confidence interval of 74.3-80.7%) and a P-value (calculated using Hosmer-Lemeshow goodness-of-fit) of 0.20. Because of the inconvenience associated with the two-hour glucose tolerance test, as well as the cost of the test, the test is seldom used in routine clinical practice. Moreover, patients whose Diabetes is diagnosed solely on the basis of an oral glucose tolerance test have a high rate of reversion to normal on follow-up and may in fact represent false-positive diagnoses (Burke et al., Diabetes Care 21:1266-1270 (1998)). Stern and others reported that such cases were almost 5 times more likely to revert to non-diabetic status after 7 to 8 years of follow-up compared with persons meeting conventional fasting or clinical diagnostic criteria.
Beyond glucose and HBA1c, several single time point biomarker measurements have been attempted for the use of risk assessment for future Diabetes. U.S. Patent Application No. 2003/0100486 proposes C-Reactive Protein (CRP) and Interleukin-6 (IL-6), both markers of systemic inflammation, used alone and as an adjunct to the measurement of HBA1c. However, for practical reasons relating to clinical performance, specifically poor specificity and high false positive rates, these tests have not been adopted.
Often a person with impaired glucose tolerance will be found to have at least one or more of the common arteriovascular disease risk factors (e.g., dyslipidemia and hypertension). This clustering has been termed “Syndrome X” or “Metabolic Syndrome” by some researchers, and can be indicative of a diabetic or pre-diabetic condition. Alone, each component of the cluster conveys increased arteriovascular and diabetic disease risk, but together as a combination they become much more significant. This means that the management of persons with hyperglycemia and other features of Metabolic Syndrome should focus not only on blood glucose control, but also include strategies for reduction of other arteriovascular disease risk factors. Furthermore, such risk factors are non-specific for Diabetes or pre-Diabetes and are not in themselves a basis for a diagnosis of Diabetes, or of diabetic status.
Risk prediction for Diabetes, pre-Diabetes, or a pre-diabetic condition can also encompass multi-variate risk prediction algorithms and computed indices that assess and estimate a subject's absolute risk for developing Diabetes, pre-Diabetes, or a pre-diabetic condition with reference to a historical cohort. Risk assessment using such predictive mathematical algorithms and computed indices has increasingly been incorporated into guidelines for diagnostic testing and treatment, and encompass indices obtained from and validated with, inter alia, multi-stage, stratified samples from a representative population. A plurality of conventional Diabetes risk factors is incorporated into predictive models. A notable example of such algorithms include the Framingham Study (Kannel, W. B. et al. (1976) Am. J. Cardiol. 38: 46-51) and modifications of the Framingham Study, such as the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III).
Other Diabetes risk prediction algorithms include, without limitation, the San Antonio Heart Study (Stern, M. P. et al. (1984) Am. J. Epidemiol. 120: 834-851; Stern, M. P. et al. (1993) Diabetes 42: 706-714; Burke, J. P. et al. (1999) Arch. Intern. Med. 159: 1450-1456), Archimedes (Eddy, D. M. and Schlessinger, L. (2003) Diabetes Care 26(11):3093-3101; Eddy, D. M. and Schlessinger, L. (2003) Diabetes Care 26(11):3102-3110), the Finnish-based Diabetes Risk Score (Lindström, J. and Tuomilehto, J. (2003) Diabetes Care 26(3): 725-731), and the Ely Study (Griffin, S. J. et al. (2000) Diabetes Metab. Res. Rev. 16:164-171), the contents of which are expressly incorporated herein by reference.
Despite the numerous studies and algorithms that have been used to assess the risk of Diabetes, pre-Diabetes, or a pre-diabetic condition, a need exists for accurate methods of assessing such risks or conditions. Furthermore, due to issues of practicality and the difficulty of the risk computations involved, there has been little adoption of such an approach by the primary care physician that is most likely to initially encounter the pre-diabetic or undiagnosed early diabetic. Clearly, there remains a need for more practical methods of assessing the risk of future Diabetes.
It is well documented that pre-Diabetes can be present for ten or more years before the detection of glycemic disorders like Diabetes. Treatment of pre-diabetics with drugs such as acarbose, metformin, troglitazone and rosiglitazone can postpone or prevent Diabetes; yet few pre-diabetics are treated. A major reason, as indicated above, is that no simple and unambiguous laboratory test exists to determine the actual risk of an individual to develop Diabetes. Furthermore, even in individuals known to be at risk of Diabetes, glycemic control remains the primary therapeutic monitoring endpoint, and is subject to the same limitations as its use in the prediction and diagnosis of frank Diabetes. Thus, there remains a need in the art for methods of identifying, diagnosing, and treating these individuals who are not yet diabetics, but who are at significant risk of developing Diabetes.
Tethys Bioscience continues to develop predicted test for Diabetes based on protein biomarkers, e.g. see WO 2007/044860.
Type 2 Diabetes and Lipid Metabolism
More than one mechanism for the development of Type 2 diabetes exists. While all of the genetic causes and environmental factors involved in development of insulin resistance are unknown, impaired lipid metabolism has been shown to play an important role in the development of Type 2 diabetes. Increased fasting plasma fatty acids are correlated with the development of obesity and insulin resistance in many populations and are an independent predictor of the development of Type 2 diabetes.
One hypothesis for the development of increased plasma fatty acids and insulin resistance starts with the adipose tissue. Enlarged adipocytes release inflammatory cytokines into the plasma which feed back to alter the adipose and other tissues' response to insulin. As the adipocytes become insulin resistant, they are unable to suppress lipolysis in response to insulin. These adipocytes are also unable to store additional fat, consequently reducing the uptake of fatty acids after a meal, resulting in excess fatty acids in the plasma. The overwhelming amount of fatty acids released by adipose tissue chronically increases plasma levels and diverts lipid into other tissues including liver, muscle, and pancreas.
In the liver, the increased fatty acids stimulate gluconeogenesis and glucose output from the liver. Chronic hyperinsulinemia and high plasma glucose concentrations stimulate liver de novo production of fatty acids. While the actual amount of fatty acids produced de novo is small, the conditions that increase fatty acid production also decrease liver fatty acid oxidation. This results in higher triglyceride esterification rates and increased availability of triglyceride for very low density lipoprotein synthesis and secretion. Along with the additional available substrate, decreased hepatocyte responsiveness to insulin may also increase release of very low density lipoprotein. The additional lipoprotein lipid released from the liver becomes substrate for lipase activity and release of free fatty acids into the plasma creating a positive feedback loop.
In the muscle, increased free fatty acids and intramuscular lipid is strongly correlated with impaired glucose metabolism. The muscle responds to chronically increased plasma fatty acids by decreasing glucose uptake, thus increasing fasting and postprandial plasma glucose concentrations. Muscle tissue may also increase uptake and decrease oxidation of the fatty acids, resulting in increased intramuscular lipid. The decreased oxidative capacity of the muscle is due to dysfunctional mitochondria, although whether this is caused by the insulin resistant state, or a cause of it, is unknown.
Peripheral insulin resistance can exist without the development of overt diabetes. Development of Type 2 diabetes occurs when the pancreatic β-cells fail to compensate for insulin resistance by increasing insulin output. The progression to diabetes is accompanied by loss of pancreatic β-cells as well as an increase in the basal rate of insulin secretion by the remaining cells, and the inability of these cells to respond to glucose. The loss of function and cell death is due to chronic exposure of β-cells to high levels of both fatty acids and glucose. Similar to the muscle, β-cells exposed to high concentrations of fatty acids have decreased lipid oxidation and increased intracellular triglycerides.
Type 2 diabetes is a disease of lipid metabolism as well as glucose metabolism. While there are multiple mechanisms for the development of insulin resistance and Type 2 diabetes, alterations in lipid metabolism is a common theme. Even though there are differences between individuals and groups of individuals in exactly how lipid metabolism is altered, disordered lipid storage and metabolism occurs at very early stages of insulin resistance in all individuals with insulin resistance and could be considered a marker of the disease. By monitoring lipid metabolites and whole-body lipid metabolism, it may be possible to define the alterations in lipids that occur with insulin resistance and Type 2 diabetes, segregate groups of patients by their changed lipid metabolism, and predict who would respond to therapy. Some lipids have been identified which predict the development of insulin resistance or diagnosis of insulin sensitivity. However, the combination of specific lipids that improves the prediction of insulin resistance or diagnosis of a diabetic condition has not been previously shown.
What is needed are better testing methods that can be used to classify, diagnose, and monitor patients at risk of developing diabetes.